Creating a map using ggplot2

library(pacman)

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library(tidyverse)

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library(dplyr)
library(plotly)

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library(DT)

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A Simple World Map

map <- map_data("world")
ggplot(map, aes(x=long, y=lat, group=group))+geom_polygon(fill="lightblue", color="white")+theme_void()

A Map for Specific Regions

North_Asia <- c("China", "Japan", "Mongolia", "North Korea", "South Korea", "Taiwan")
North_Asia_map <- map_data("world", region= North_Asia)
region.data <- North_Asia_map %>% group_by(region) %>% summarize(long=mean(long), lat=mean(lat)) %>% arrange()
ggplot(North_Asia_map, aes(x=long, y=lat))+geom_polygon(aes(group=group, fill=region))+geom_text(data=region.data, aes(label=region), size=5, hjust=0.5, col="#808080", fontface="bold")+scale_fill_viridis_d()+theme_void()+theme(legend.position="none")

A Chloropleth Map

drinks <- read.csv('./drinks.csv')
drinks_map <- drinks %>% left_join(map, by =c("country"="region"))
ggplot(drinks_map, aes(long, lat, group=group))+geom_polygon(aes(fill=total_litres_of_pure_alcohol),color="white")+scale_fill_viridis_c(option="C")+labs(fill="Total Litres of Pure Alcohol")+theme_void()+theme(legend.position="bottom")

ggplot(drinks, aes(map_id=country))+geom_map(aes(fill=total_litres_of_pure_alcohol), map= map, color="white")+expand_limits(x=map$long, y=map$lat)+labs(fill="Total Litres of Pure Alcohol")+theme_void()+theme(legend.position="bottom")

ggplot(drinks, aes(map_id=country))+geom_map(aes(fill=total_litres_of_pure_alcohol), map=map, color="white")+expand_limits(x=map$long, y=map$lat)+labs(fill="Total Litres of Pure Alcohol")+theme_void()+theme(legend.position="bottom")

A U.S. State-Level Map

US_map <- map_data("state")

state_data<- US_map %>% filter(region != "district of columbia") %>% group_by(region) %>% summarize(long=mean(long), lat=mean(lat)) %>% arrange(region)

state_data$region.abb <- state.abb[-c(2,11)] #drop Alaska and Hawai'i
p<- ggplot(US_map, aes(x=long, y=lat))+geom_polygon(aes(group=group,fill=region), color="white")+geom_text(data=state_data, aes(label=region.abb), fontface="bold")+theme_void()+theme(legend.position="none")
p

A Dynamic Map using plotly - 1

library(plotly)
ggplotly(p)

A Dynamic Map using plotly - 2

crimes <- data.frame(region=rownames(USArrests), USArrests) %>% filter(region!=c("Alaska", "Hawaii"))

crimes$region<- tolower(crimes$region)
crimes_map <- crimes %>% left_join(US_map, by="region")

g1<- ggplot(crimes_map, aes(x=long, y=lat))+
  geom_polygon(aes(group=group, fill=Murder,
                   text = paste0(region, ":\n",
                  Murder, "murder arrests per 100,000"),
                  color="white"))+
  geom_text(data=state_data,
            aes(label=region.abb), fontface="bold", size=3)+
  scale_fill_viridis_c(option="C")+theme_void()

## Warning in geom_polygon(aes(group = group, fill = Murder, text = paste0(region,
## : Ignoring unknown aesthetics: text

ggplotly(g1, tooltip="text")

A County-Level Map

covid <- read_csv("./COVID19.csv")

## Rows: 1175665 Columns: 30
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr   (4): id, administrative_area_level_1, administrative_area_level_2, adm...
## dbl  (25): confirmed, deaths, people_vaccinated, people_fully_vaccinated, sc...
## date  (1): date
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ohio <- covid %>% filter(administrative_area_level_2=="Ohio", date=="2021-12-31")

ohio <- ohio %>% rename(county=administrative_area_level_3)

ohio_county <- map_data("county", region= "ohio")
ohio_county$subregion <- str_to_title(ohio_county$subregion)

ohio_map <- ohio %>% left_join(ohio_county, by=c("county"="subregion"))

g2 <- ggplot(ohio_map, 
             aes(x= long, y= lat))+
  geom_polygon(aes(group=group, fill=deaths,
                   text=paste0("County: ", county, "\n",
                               "Total Deaths: ", deaths)))+
  geom_text(data=ohio, aes(x= longitude, y=latitude, label=county),
            color="white", fontface="bold")+
  scale_fill_viridis_c(option="H")+
  theme_minimal()+theme_void()

## Warning in geom_polygon(aes(group = group, fill = deaths, text =
## paste0("County: ", : Ignoring unknown aesthetics: text

font <- list(family="Arial", size=15, color="white")
label <- list(bgcolor="#232F34", bordercolor="transparent", font=font)
ggplotly(g2, tooltip="text", width=850, height=800) %>% style(hoverlabel=label) %>% layout(font=font)